Analyse, Bewertung und Steuerung der durch die Implementierung von Robotic Process Automation (RPA) in deutschen Großbanken entstehenden operationellen Risiken – Eine theoretische Konzeption, empirische Evaluierung und anwendungsorientierte Gestaltung

The largest German banks, as leaders in the country's banking landscape, face a critical juncture where tradition intersects with digitalization. Navigating this transformation is crucial for maintaining relevance while meeting the growing demand for seamless digital services. Robotic Process Automation (RPA) is seen as a promising solution for enhancing efficiency and fostering innovation. However, the associated automation risks require proper risk management. This research examines the intersection of RPA and operational risk management, investigating how established risk management frameworks can be applied to the RPA lifecycle without compromising compliance or overcomplicating processes. Emphasizing a comprehensive risk management approach, this case study covers the entire process from identification to control, ensuring a more integrated and effective risk management by addressing each phase holistically.

The theoretical section identifies 30 risk scenarios within the RPA lifecycle and outlines 17 Success Factors (SFs) essential for realizing RPA benefits by directly or indirectly impacting the return on investment (ROI). These elements form the foundation for the empirical study, which is conducted as a mixed-methods case study.

In Part A of this study, data from 200 real-world RPA use cases across six ECB-supervised German banks were analyzed using SPSS, identifying six key CSFs: economic viability, the underlying process, IT security, roles and responsibilities, employee skills, engagement, and alignment and complexity of affected applications. In Part B, eight semi-structured expert inter-views revealed 25 operational risk scenarios, leading to the creation of a risk catalog as the basis for conducting Risk and Control Self-Assessments (RCSAs).

Based on the empirical research results, a holistic risk management approach was developed by examining the impact of risk scenarios on the six CSFs. The findings demonstrate how risk management elements—identification, measurement, and control—interact within the RPA lifecycle. A four-phase model illustrates these insights, providing a practical framework for managing operational risks in RPA implementations. Furthermore, an interactive measurement approach, based on the six CSFs, was established to assess, prioritize, and monitor RPA use cases. This comprehensive approach addresses the core research question of how to effectively identify, assess, and manage operational risks in RPA implementation within ECB-supervised banks in Germany.